(New page: Question 1 Question 2 Question 3 Question 4 Question 5)
 
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Additional information for the first lab (if you are still unsure of what FIR and IIR):
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Compiler: Read through "Makeflie" and google "linux make"
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FIR: consider a sliding window pass through the entire image defined as h(m,n) that could be transformed to H(u,v)
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IIR: H(u,v) is defined as Y(u,v)/X(u,v) which is transformed from y(m,n)/x(m,n)
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Some easy checks you could perform yourself:
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Low Pass Filter: Smoothing (less sharp edges or details but reduces some static noise)
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High Pass Filter: Sharping (clear edge and enhance details but also emphasize noise)
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Rule of thumb:If your image doesn't look like it is doing what it is supposed to do, it is probably wrong.
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In this case, you want to first make sure your MATLAB functions shows the right result before C
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Then check all your buffers with compilation
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Question 1
 
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Revision as of 14:49, 17 January 2013

Additional information for the first lab (if you are still unsure of what FIR and IIR): Compiler: Read through "Makeflie" and google "linux make" FIR: consider a sliding window pass through the entire image defined as h(m,n) that could be transformed to H(u,v) IIR: H(u,v) is defined as Y(u,v)/X(u,v) which is transformed from y(m,n)/x(m,n)

Some easy checks you could perform yourself: Low Pass Filter: Smoothing (less sharp edges or details but reduces some static noise) High Pass Filter: Sharping (clear edge and enhance details but also emphasize noise)

Rule of thumb:If your image doesn't look like it is doing what it is supposed to do, it is probably wrong. In this case, you want to first make sure your MATLAB functions shows the right result before C Then check all your buffers with compilation

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Alumni Liaison

Sees the importance of signal filtering in medical imaging

Dhruv Lamba, BSEE2010